We are looking for an innovative Senior AI ML Engineer to join our team πΆπ. You'll build an AI agent for the Model Factory Lab (MFL) community that turns a natural-language prompt into a fully instantiated model β orchestrating reusable catalog components under the βmodel as a YAMLβ paradigm.
This role works closely with the MFL platform team, combining agent development with a deep understanding of model packaging and reusable, governed components. Strong technical creativity and a product mindset are essential to succeed in this fast-paced, collaborative environment.
Leveraging our expertise, we build modern Machine Learning systems for demand planning and budget forecasting.
Developing scalable data infrastructures, we enhance high-level decision-making, tailored to each client.
Offering comprehensive Data Engineering and custom AI solutions, we optimize cloud-based systems.
Using Generative AI, we help e-commerce platforms and retailers create higher-quality ads, faster.
Building deep learning models, we enhance visual recognition and automation for various industries, improving product categorization, quality control, and information retrieval.
Developing recommendation models, we personalize user experiences in e-commerce, streaming, and digital platforms, driving engagement and conversions.
Amazon Web Services
Astronomer
Databricks
π We are Data Nerds
π€ We are Open Team Players
π We Take Ownership
π We Have a Positive Mindset
π Curious about what weβre up to? Check out
our case studies and dive into our
blog post to learn more about our culture and the exciting projects weβre working on! π
Design and build the agent that translates natural language into a composition of trainable components (train/predict/evaluate), following the MFL development framework (PyFunc / custom flavor as standard).
Implement the model's declarative configuration in YAML (config.yaml, features.yaml, databricks.yml), respecting the MFL's minimum library skeleton.
Integrate the agent with Feature Store, MLflow, and model orchestration to assemble governed, reusable components.
Apply production-grade agentic patterns on Databricks (Mosaic AI Agent Framework, Agent Bricks, MCP Servers, evaluation with MLflow 3.0).
Experience developing AI agents, ideally on Databricks (Mosaic AI, LangGraph / OpenAI SDK, Genie, Vector Search).
Strong command of MLflow (tracking, registry, pyfunc / custom flavor), Unity Catalog, and advanced Python.
Understanding of component-orchestration architectures and model packaging.
Experience with MCP, RAG, agent evaluation, and model governance standards.
Broader experience developing AI agents / agentic infrastructure (Mosaic AI Agent Framework, agent orchestration, MCP).
Remote-first culture β work from anywhere! π
AWS, DBT, Google Cloud, Azure & Databricks certifications fully covered
Birthday off + an extra vacation week (Mutt Week! ποΈ)
Referral bonuses β help us grow the team & get rewarded!
Maslow: Monthly credits to spend in our benefits marketplace.
βοΈποΈ Annual Mutters' Trip β an unforgettable getaway with the team!
